Abstract
Vehicle safety remains a topic of major interest, and diverse assistance systems are implemented that focus primarily on analyzing the immediate vicinity of the car and the driver’s control inputs. In this paper, by contrast, we emphasize understanding the driver’s control performance via obtaining valuable data and relevant characteristics. To acquire the data, we employed an in-house-designed, laboratory-built vehicle driving simulator. This simulator exploits the Unreal Engine 4 framework to deliver a high level of realism. The fact that the actual designing and associated processes were materialized through our own efforts has brought advantages such as simplified data acquisition, possibility of creating custom scenarios, and modification of the virtual elements according to our specific needs. We also developed an application to analyze the measured data from the perspective of control theory, establishing a set of parameters that provided the basis for an early version of a driver performance index indicator.
Funder
SECREDAS Product Security for Cross Domain Reliable Dependable Automated System, H2020-ECSEL, EU
Subject
Public Health, Environmental and Occupational Health,Safety Research,Safety, Risk, Reliability and Quality
Cited by
10 articles.
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